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The thermal decomposition of the thermodynamic, kinetic and mechanisms of copolymer P(DAC-AM) samples with serial cationicity and intrinsic viscosity ([η]), and the control samples of homopolymer PAM and PDAC, were studied and analyzed using TG, DSC, FTIR. The results of the thermal decomposition thermodynamics confirmed that the thermal decomposition processes of the serial P(DAC-AM) samples and the two control samples could be divided into two stages. It was found that the processes of the copolymer P(DAC-AM) samples were not a simple superposition of those of homopolymers, whose monomers had composed the unit structures of the copolymer, but there were interactions between the two suspension groups. The results of thermal decomposition kinetics showed that the apparent activation energy (E) of the thermal decomposition process of all polymer samples had different varying trends in the terms of weight-loss rate (α). The reaction order (n) of the thermal decomposition of P(DAC-AM) in Stage I and II was close to 1, but in the former and the latter it tended to be 2 and 0.5, respectively. Finally, the thermal decomposition mechanism of copolymer P(DAC-AM) samples was discussed. The above research could not only fill in the knowledge vacancy of the thermal decomposition of the thermodynamic, kinetic and mechanisms of P(DAC-AM), but could also lay a foundation for the study of thermal decomposition mechanisms of the other types of polymers, including cationic polymers. [ABSTRACT FROM AUTHOR]

Sampling design plays a critical role in farm-level digital soil mapping (DSM). In many cases, a soil mapping model may not have been decided upon at the sample design stage. Design-based sampling may be more appropriate than model-based sampling because it is independent of subsequent soil mapping models. However, existing sampling methods optimize the sample size and locations in geographical space or feature space without considering the impacts of environmental similarity in local geographical space. In this paper, a novel sampling design method based on local environmental similarity was developed. Image segmentation was introduced into the sampling design by partitioning agricultural soil into subregions with good spatial continuity, within-region homogeneity, and between-region heterogeneity to determine the optimal sample size and locations. First, the environmental similarity between adjacent soils was calculated. Second, the merging process was iteratively conducted, and a series of segmentations was generated. Finally, the optimal sample size and locations were determined based on the optimal segmentation results. To validate the proposed method, it was compared with stratified random sampling, k-means sampling, and spatially balanced sampling methods. Two mapping models, ordinary kriging and sandwich estimation, were employed to map five soil properties, including pH, soil organic matter, total nitrogen, available phosphorus, and available potassium. These comparative experiments showed that the proposed method had better potential to generate farm-level muti-soil property mapping results with good accuracy than the competing sampling methods. In conclusion, consideration of local environmental similarity and the use of image segmentation for soil sampling were helpful in determining the optimal sample size and key sample locations. [ABSTRACT FROM AUTHOR]

Leonurus japonicus Houtt. is a traditional Chinese medicinal plant with high medicinal and edible value. Wild L. japonicus resources have reduced dramatically in recent years. This study predicted the response of distribution range of L. japonicus to climate change in China, which provided scientific basis for the conservation and utilization. In this study, 489 occurrence points of L. japonicus were selected based on GIS technology and spThin package. The default parameters of MaxEnt model were adjusted by using ENMeva1 package of R environment, and the optimized MaxEnt model was used to analyze the distribution of L. japonicus. When the feature combination in the model parameters is hing and the regularization multiplier is 1.5, the MaxEnt model has a higher degree of optimization. With the AUC of 0.830, our model showed a good predictive performance. The results showed that L. japonicus were widely distributed in the current period. The maximum temperature of warmest month, the min temperature of coldest month, the precipitation of wettest month, the precipitation of driest month, and altitude were the main environmental factors affecting the distribution of L. japonicus. Under the three climate change scenarios, the suitable distribution area of L. japonicus will range shift to high latitudes, indicating that the distribution of L. japonicus has a strong response to climate change. The regional change rate is the lowest under the SSP126‐2090s scenario and the highest under the SSP585‐2090s scenario. [ABSTRACT FROM AUTHOR]

Soil sampling is critical to obtaining reliable input for farm field-level digital soil mapping (DSM). Sample size and location are the key issues for soil sampling. However, sample size is often restricted by available budgets. In this case, recognizing the key sample locations is necessary. Existing methods have optimized the sample locations in a global manner without considering the impacts of local heterogeneity of soil. In this paper, a novel sampling approach based on the local heterogeneity of soil with a limited sample size (40 samples in this research) was developed. First, the local heterogeneity of soil was inferred. Second, the sub-regions were divided based on the level of local soil heterogeneity and the corresponding sample numbers were determined. Finally, the key sample locations were determined based on the fuzzy memberships. To validate the proposed method, it was compared with stratified random sampling, k-means sampling and conditional Latin hypercube sampling. The ordinary kriging method was applied to map five soil properties, including soil organic matter, pH, total nitrogen, available phosphorus and available potassium. The comparative experiments showed that the proposed method has better robustness in satisfying good mapping accuracy for multi-soil properties at the farm field level compared with the competing sampling methods, as indicated by the relatively lower and more stable mean bias error (MBE) and root mean square error (RMSE) values. It can be concluded that the consideration of local heterogeneity of soil is helpful to recognize the key sample locations for limited sample sizes. [ABSTRACT FROM AUTHOR]

Poly(3-methacrylamido propyl trimethyl ammonium chloride) (PMAPTAC) is a typical cationic water-soluble polyelectrolyte, which has been widely used in petroleum, papermaking, daily cosmetics and other fields in the form of an aqueous solution. However, the acid–base and thermal stability of PMAPTAC in aqueous solution have not been reported yet, which hinders its further application in high-temperature and acid–base environments. To address these deficiencies, the effects of temperature and pH of PMAPTAC with different intrinsic viscosities on its hydrolysis stability were investigated qualitatively and quantitatively, and the hydrolysis mechanism was studied. Firstly, the qualitative analysis showed that the apparent viscosity of the PMAPTAC solution decreased with hydrolysis time at different temperatures and pH. The higher the temperature and the lower the pH, the greater the viscosity loss of PMAPTAC. The quantitative analysis showed that the hydrolysis rate of the PMAPTAC sample solution increased with the increase in temperature and pH. In addition, the intrinsic viscosity of PMAPTAC samples had little effect on the hydrolytic stability of PMAPTAC. Secondly, by analyzing the viscosity curves at different pH and temperatures by Arrhenius analysis, the Arrhenius equations were found to be 1/τ = 200.34e^((−25.04)/RT), 1/τ = 9127.07e^((−38.90)/RT) and 1/τ = 4683.03e^((−39.89)/RT) for pH 3, pH 7 and pH 11, respectively. Thirdly, the hydrolysis rate of PDMC was the fastest under alkaline conditions. In addition, compared with PDMC, PMAPTAC had better hydrolysis stability under the same conditions. Finally, the mechanism of the hydrolyzed polymer was studied by FTIR and 13CNMR, which showed that the carbonyl group of PMAPTAC was hydrolyzed into a carboxyl group, and the small molecule (3-aminopropyl) trimethylammonium chloride was generated, while the ester group of PDMC was hydrolyzed into a carboxyl group, and choline chloride was released. The above results can provide a theoretical basis for the application of PMAPTAC in some high-temperature and acid–base environments. [ABSTRACT FROM AUTHOR]

In this paper the thermal stability properties of poly(3-methacryloylamino propyl trimethyl ammonium chloride) (PMAPTAC) with a series of molecular weights in various salt solutions were investigated by monitoring the apparent viscosity and viscosity retention rate with aging time, for the first time to our knowledge. Secondly, the thermal stability properties of poly(methacryloyloxy ethyl trimethyl ammonium chloride) (PDMC) solution was studied and compared with that of the PMAPTAC solution under the same conditions. The results showed that the viscosity retention rate of PMAPTAC/salt solutions with salinities from 40 g/L to 200 g/L at 85 °C were about 60%, indicating that PMAPTAC had good temperature and salt resistance. Besides, the temperature and salt resistance of PMAPTAC with 0.62 dL/g was better than that of PMAPTAC with 7.55 dL/g under the conditions of this study. In addition, the viscosity retention rate of PDMC/salt solution with the same intrinsic viscosity as PMAPTAC/salt solution was 45%, indicating that compared with PDMC, the PMAPTAC with viscosity retention rate of 60% had better temperature and salt resistance. We suggest the results obtained in this study will not only fill the current gaps in the research of the temperature and salt tolerance properties of PMAPTAC, but also provide support for the potential application of PMAPTAC products in high-temperature and high-salt environments. [ABSTRACT FROM AUTHOR]

Deep learning techniques are increasingly applied to scientific problems, where the precision of networks is crucial. Despite being deemed as universal function approximators, neural networks, in practice, struggle to reduce the prediction errors below O (10 − 5) even with large network size and extended training iterations. To address this issue, we developed the multi-stage neural networks that divides the training process into different stages, with each stage using a new network that is optimized to fit the residue from the previous stage. Across successive stages, the residue magnitudes decreases substantially and follows an inverse power-law relationship with the residue frequencies. The multi-stage neural networks effectively mitigate the spectral biases associated with regular neural networks, enabling them to capture the high frequency feature of target functions. We demonstrate that the prediction error from the multi-stage training for both regression problems and physics-informed neural networks can nearly reach the machine-precision O (10 − 16) of double-floating point within a finite number of iterations. Such levels of accuracy are rarely attainable using single neural networks alone. • We introduced multi-stage neural network (MSNN) to boost training accuracy. • In each stage a new NN is trained to fit the residues from the previous stage. • Optimal settings were devised to minimize errors at each stage of training. • MSNN mitigates spectral biases and accurately captures high-frequency functions. • MSNN achieved unprecedented accuracy, approaching machine precision. [ABSTRACT FROM AUTHOR]

Chemical doping is a powerful way to enhance the electrical performance of organic electronics. To avoid perturbing the ordered molecular packing of organic semiconducting hosts, molecular dopants are deposited on the surface of highly crystalline organic semiconductor thin films. However, such surface doping protocols not only limit charge‐transfer efficiency but also cause dopant diffusion problems, which significantly reduce charge carrier mobility and device stability. Here, an innovative anion bulk doping strategy is reported that allows effective doping of organic single‐crystalline films (OSCFs) without disrupting molecular ordering to improve the performance of organic field‐effect transistors (OFETs). This method is mediated by anion dopants and can be pictured as an effective charge transfer of dopants with organic semiconductors in liquid phase. The direct introduction of dopant anions overcomes limitations of partial charge transfer while avoiding interference from dopant aggregation with crystallization. Using this method, the average carrier mobility of the OSCFs is boosted by ≈2.5 times. Significantly, low‐voltage OFETs developed from anion‐doped OSCFs exhibit a near‐ideal subthreshold swing of 59.2 mV dec−1 and unparalleled mobility as high as 19.8 cm2 V−1 s−1 together with excellent stability. The concept of anion doping opens new avenues for improving the electrical performance of organic electronics. [ABSTRACT FROM AUTHOR]

Crystal phase, a critical structural characteristic beyond the morphology, size, dimension, facet, etc., determines the physicochemical properties of nanomaterials. As a group of layered nanomaterials with polymorphs, transition metal dichalcogenides (TMDs) have attracted intensive research attention due to their phase-dependent properties. Therefore, great efforts have been devoted to the phase engineering of TMDs to synthesize TMDs with controlled phases, especially unconventional/metastable phases, for various applications in electronics, optoelectronics, catalysis, biomedicine, energy storage and conversion, and ferroelectrics. Considering the significant progress in the synthesis and applications of TMDs, we believe that a comprehensive review on the phase engineering of TMDs is critical to promote their fundamental studies and practical applications. This Review aims to provide a comprehensive introduction and discussion on the crystal structures, synthetic strategies, and phase-dependent properties and applications of TMDs. Finally, our perspectives on the challenges and opportunities in phase engineering of TMDs will also be discussed. [ABSTRACT FROM AUTHOR]

The corrosion resistance and wear resistance of magnesium alloys seriously restrict their applications in industry. The objective of this work is to provide a comprehensive understanding, including parameters, microstructure and properties, of the cold arc cladding process of aluminum coatings on AZ61 magnesium alloy. Three kinds of cladding wires, Al-Mn alloy (AlMn1), Al-Si alloy (AlSi5) and Al-Mg alloy (AlMg5), were cladded on the surface of AZ61 magnesium alloy by pulsed direct current (P-DC) cold arc for a comparative study. The study revealed a correlated relation between the clad geometry and the heat input during the deposition process. The microstructure and composition of the coatings were carefully studied by SEM, EDS and XRD. The properties of the coatings were studied by the micro-hardness, wear resistance and electrochemical corrosion test. The Al-Mn alloy coating has the highest hardness, which is three times that of the AZ61 magnesium matrix. The Al-Si alloy coating has the lowest wear rate, which is about 13.9% of the Mg matrix. The corrosion performance of the Al-Mg alloy coatings is significantly improved byα-Al phase compared to the Mg matrix. • Three aluminum alloy coatings were prepared by cold arc cladding for a comparative study. • Provides a comprehensive understanding of the cold arc cladding process • The flow model for the melted pool of the cold arc cladding process is given. • The hardness and corrosion resistance of the three coatings are greatly improved. [ABSTRACT FROM AUTHOR]

• Proposed method considers the contribution of local spectral information in homogeneity and heterogeneity indicators. • BSH indicator is proposed for heterogeneity calculation. • Contribution of the common border between one segment and its neighbors is considered in BSH calculation. • Proposed method is more potential for determining appropriate segmentation parameter. Image segmentation is a key issue in geographic object-based image analysis, thus determining the appropriate segmentation parameter is a prerequisite to allowing for obtaining accurate segmentation. In this study, an unsupervised segmentation parameter selection method using the local spatial statistics was proposed for achieving the automatic parameter optimization of image segmentation. The two measure of within-segment homogeneity (WSH) and between-segment heterogeneity (BSH) were calculated using local spatial statistics approach, and then integrated into a global value for indicating the overall segmentation quality. In addition, the contribution of the common boundary between each segment and one of its neighboring segments was considered in BSH calculation for obtaining a more objective evaluation. For this experiment, the multi-resolution segmentation (MRS) method was used as a segmentation algorithm and GF-1 image used as test data. The measure analysis experiment of the proposed method showed BSH is more sensitive to under-segmentation. The visual and discrepancy measures results of the proposed method compared with the other four methods revealed that the proposed method is more potential to recognize the proper segmentation parameter with the purpose of allowing for obtaining segmentations with high quality. [ABSTRACT FROM AUTHOR]

Abstract: The reproductive stages of the life cycle are crucial in explaining the distribution patterns of plant species because of their extreme vulnerability to environmental conditions. Despite reported evidence that seed germination is related to habitat macroclimatic characteristics, such as mean annual temperature, the effect of this trait in controlling plant species distribution has not yet been systematically and quantitatively evaluated. To learn whether seed germination can predict species distribution along altitude gradients, we examined germination data of 36 Rhododendron species in southeastern Tibet originating from contrasting altitudes, habitats, plant heights, seed masses, and phylogenies. Germination varied significantly with altitude, habitat, plant height, and phylogeny and was higher in the light than in the dark. Germination percentage was highest at 10:20°C in the light and 15:25°C in the dark. As altitude increased, germination percentages first rose and then decreased, being highest at 3,500–4,000 m. Germination percentage and rate were highest on rocky slopes, increasing as seed mass and plant height rose. Variations in germination percentage and rate were not significant at subgenera, section, and subsection levels, but they were significant at species level. The results suggested that the relationship between germination and altitude may provide insights into species distribution patterns. Further, germination patterns are a result of long‐term evolution as well as taxonomic constraints. [ABSTRACT FROM AUTHOR]

• Soil sample outlier recognition method from geographical perspective is proposed. • It can fully excavate the local spatial structure information of soil sample data. • Spatial search distance is automatically determined by the spatial distance among soil samples. • Spatial autocorrelation and heterogeneity are considered to calculate outlier scores. • Threshold to potential outliers in soil datasets was determined by a frequency histogram. Soil datasets with outliers lead to inaccurate farm-level digital soil mapping (DSM) results. Existing methods identify potential outliers in soil datasets based on expert experience or simple statistics that neglect the geographical characteristics of soil. In this paper, a novel potential outlier recognition method was developed from the perspective of geographical context. First, spatial search distance was automatically determined by the spatial distance among soil samples. Second, similarities of adjacent soil samples and the local spatial variation level were comprehensively considered to calculate outlier scores. Finally, a frequency histogram of outlier scores was generated to determine a suitable threshold for recognizing potential abnormal samples. To validate the proposed method, it was compared to Lambda and Box-Plot methods, and the ordinary kriging method was used to map five soil properties, including pH, soil organic matter, total nitrogen, available phosphorus and available potassium, in an agricultural region. Then, a synthetic study using artificially contaminated DEM data was also conducted. The comparative experiment shows that the proposed method is better able to recognize potential outliers by mining the local spatial structure, as indicated by lower mean absolute error (MAE) and root mean square error (RMSE) values. It can be concluded that consideration of local spatial autocorrelation and heterogeneity is helpful in recognizing potential outliers. [ABSTRACT FROM AUTHOR]

A novel temperature-resistant fluid loss reducer FL is obtained by free radical copolymerisation. Thermal gravimetric analysis demonstrates that the fluid loss reducer FL has a strong temperature-resistance capability and its degradation temperature is higher than 440°C. An experiment investigating the effect of FL on the comprehensive performance of oil well cement slurry shows that filter loss can be controlled within 50 ml when the dosage of FL is 1·0% of the total mass of cement and quartz powder under the ultra-high-temperature condition of 200°C (bottom-hole circulating temperature). Cement slurry with FL exhibits good comprehensive performance under high-temperature and ultra-high-temperature conditions. The working mechanisms of the fluid loss reducer FL are studied and the compressible 'viscoelastic adsorbed layer' perspective is proposed, which could explain the excellent ability to control the filter loss of cement slurry under high temperature. [ABSTRACT FROM AUTHOR]

• The longitudinal swirling flows is formed for heat transfer enhancement. • The temperature gradient of the tube wall is increases significantly. • Nu and f are enhanced by 5.00–10.22 and 4.05–14.20 times, respectively. • The range of the efficiency evaluation criterion is 0.71–1.35. • The Non-dominated sorting genetic algorithm is applied to obtain the pareto front. It is crucial to further improve the overall performance of heat exchanger tube and make it adapt to higher flux conditions. In this paper, a novel type of tube inserts, symmetrical wing longitudinal swirl generators (SWLSGs), was proposed and its thermal hydraulic performance was numerically investigated under laminar flow. The effect of four geometrical parameters (inclined angle (φ 1), face angle (φ 2), wing angle (φ 3) and pitch (P)) was explored. The results showed the mechanisms of heat transfer augmentation for SWLSGs could be divided into two main categories. The first one was that a longitudinal swirl flow with multi-vortexes would be formed by symmetrical wings. The other one was that SWLSGs had a structure similar to a deflector, which guided the cold water in the center to scour tube wall. This study found that the variation ranges of Nu/Nu 0 , f/f 0 , and the efficiency evaluation criterion (EEC) were 5.00–10.22, 4.05–14.20, and 0.71–1.35, respectively. Both exergy destruction of heat transfer and fluid flow increased as face angle and wing angle increased, and decreased as inclined angle and pitch increased. Exergy destruction minimization principle was adopted to optimize SWLSGs. After fitting function through artificial neural network, genetic algorithm was applied to obtain the Pareto front. The physical parameters of the compromised point on the Pareto front were φ 1 =25.6°, φ 2 =142.0°, φ 3 =13.4°, P = 64.7 mm, and EEC = 1.26. The EEC of the highest point of the ratio of the exergy destruction of heat transfer and fluid flow (REHF) was 1.48. The present work provided a new method for multi-parameter study of tube inserts, and proved that the exergy destruction as evaluation was an effective evaluation index for design and optimization. [ABSTRACT FROM AUTHOR]

A novel organic boron cross-linker for the polyvinyl alcohol fracturing fluid system was synthesized. The formulas of the fracturing fluid system operating at 50 and 70°C were developed. The performance of the polyvinyl alcohol fracturing fluid system at 70°C was comprehensively evaluated and compared with that of the conventional fracturing fluid. The results show that the polyvinyl alcohol fracturing fluid is mainly elastic in the range 0.01-10 Hz, and the final gel viscosity of the polyvinyl alcohol fracturing fluid is above 50 mPa s under the conditions of continuous shearing for 120 min at a shear rate of 170 s at 70°C. Thus, the fracturing fluid exhibits good temperature-shear resistance. The sedimentation rate of 60 to 80 mesh quartz sand in polyvinyl alcohol fracturing fluid is lower compared to that in the gum fracturing fluid, i.e., the sand-carrying performance is good. The polyvinyl alcohol fracturing fluid system also exhibits other favorable characteristics such as low filtration coefficient, low residue, low fluid loss, easy and thorough gel breaking, low gel-breaking liquid surface tension, and reduced damage to the stratum. Thus, polyvinyl alcohol can replace guar and its derivatives used in fracturing fluid at low temperature. The regenerative experiment with polyvinyl alcohol fracturing fluid shows that the viscoelastic characteristics, temperature-shear resistance, fracture-making ability, and sand-carrying performance decline upon regeneration. [ABSTRACT FROM AUTHOR]

This paper is a summary of the research development in the rational (total) nonlinear dynamic modelling over the last two decades. Total nonlinear dynamic systems are defined as those where the model parameters and input (controller outputs) are subject to nonlinear to the output. Previously, this class of models has been known as rational models, which is a model that can be considered to belong to the nonlinear autoregressive moving average with exogenous input (NARMAX) model subset and is an extension of the well-known polynomial NARMAX model. The justification for using the rational model is that it provides a very concise and parsimonious representation for highly complex nonlinear dynamic systems and has excellent interpolatory and extrapolatory properties. However, model identification and controller design are much more challenging compared to the polynomial models. This has been a new and fascinating research trend in the area of mathematical modelling, control, and applications, but still within a limited research community. This paper brings several representative algorithms together, developed by the authors and their colleagues, to form an easily referenced archive for promotion of the awareness, tutorial, applications, and even further research expansion. [ABSTRACT FROM PUBLISHER]

This work proposes a discrete-time nonlinear rational approximate model for the unstable magnetic levitation system. Based on this model and as an application of the input-output linearization technique, a discrete-time tracking control design will be derived using the corresponding classical state space representation of the model. A simulation example illustrates the efficiency of the proposed methodology. [ABSTRACT FROM AUTHOR]

This study addresses the cooperative control problem of multi‐missile systems. It proposed a two‐stage control strategy, aiming at simultaneous attack from a group of missiles at a static target. The first stage adopts a special distributed consensus protocol in order for all missiles to asymptotically achieve a consensus of states. During the second stage, the local sightline control law allows the missiles to independently reach the target. The dynamic equation of the missile agent is normalised to a quasi‐double‐integrator model which is convenient for designing the consensus protocol. The proposed strategy is suitable for missiles of different speeds that have been self‐organised without air operations centres. Two convincing simulation results are given to illustrate the efficiency of the proposed method. [ABSTRACT FROM AUTHOR]

The selection of certain indicators is critical to undertake ecological risk assessments of long-term oil pollution and other environmental changes. The indicators should be easily and routinely monitored, be sensitive to pollution, respond to pollution in a predictable manner, and match the spatial and temporal scales of investigations. To compare the effectiveness of indicators for the long-term risk assessments, this study investigated the multiple ecological effects of chronic oil pollution on the plant community dominated by reed ( Phragmites australis ). The physiology, growth and reproduction of reed, together with the composition and productivity of the reed community, were measured around oil wells that have operated for approximately 10 years in the Yellow River Delta, eastern China. The predictive power of each indicator was evaluated using the coefficients of determination ( R 2 ) of linear regression models established for each indicator and soil Total Petroleum Hydrocarbons (TPH) concentration. The sensitivities of indicators were evaluated by comparing slopes of new established regression lines using standardized data. The top three indicators in terms of predictive power were leaf length, width and number, followed by the Shannon–Wiener index, Pielou evenness index and Simpson's diversity index. Community aboveground biomass, foliar projective coverage and species richness showed predictive power lower than those of the three diversity indexes, but higher than those of leaf net photosynthetic rate, reed height, aboveground biomass and vertical projective coverage of reed plants. Leaf transpiration, chlorophyll concentration and reed stem density showed no significant linear response to elevated soil TPH concentration. In terms of sensitivity, the top three biological indicators were Pielou evenness index, Simpson's diversity index and Shannon–Wiener index, followed by community vertical projective coverage, community aboveground biomass, and species richness. Leaf number, length and width were moderately sensitive, followed by reed coverage, aboveground biomass and height. The sensitivity of net photosynthetic rate was the lowest. The predictive power and sensitivities of indicators were compared in terms of their spatial and temporal scales. In conclusion, scale can be used to facilitate the selection of indicators, and the combination of different indicators may yield improved understanding of the various effects of elevated soil TPH concentration at the different biological levels. [ABSTRACT FROM AUTHOR]

Seed mass and morphology are plant life history traits that influence seed dispersal ability, seeding establishment success, and population distribution pattern. Southeastern Tibet is a diversity center for Rhododendron species, which are distributed from a few hundred meters to 5500 m above sea level. We examined intra- and interspecific variation in seed mass and morphology in relation to altitude, habitat, plant height, and phylogeny. Seed mass decreased significantly with the increasing altitude and increased significantly with increasing plant height among populations of the same species. Seed mass differed significantly among species and subsections, but not among sections and subgenera. Seed length, width, surface area, and wing length were significantly negative correlated with altitude and significantly positive correlated with plant height. Further, these traits differed significantly among habitats and varied among species and subsection, but not among sections and subgenera. Species at low elevation had larger seeds with larger wings, and seeds became smaller and the wings of seeds tended to be smaller with the increasing altitude. Morphology of the seed varied from flat round to long cylindrical with increasing altitude. We suggest that seed mass and morphology have evolved as a result of both long-term adaptation and constraints of the taxonomic group over their long evolutionary history. [ABSTRACT FROM AUTHOR]

Propensity score matching is a method to reduce bias in non-randomized and observational studies. Propensity score matching is mainly applied to two treatment groups rather than multiple treatment groups, because some key issues affecting its application to multiple treatment groups remain unsolved, such as the matching distance, the assessment of balance in baseline variables, and the choice of optimal caliper width. The primary objective of this study was to compare propensity score matching methods using different calipers and to choose the optimal caliper width for use with three treatment groups. The authors used caliper widths from 0.1 to 0.8 of the pooled standard deviation of the logit of the propensity score, in increments of 0.1. The balance in baseline variables was assessed by standardized difference. The matching ratio, relative bias, and mean squared error (MSE) of the estimate between groups in different propensity score-matched samples were also reported. The results of Monte Carlo simulations indicate that matching using a caliper width of 0.2 of the pooled standard deviation of the logit of the propensity score affords superior performance in the estimation of treatment effects. This study provides practical solutions for the application of propensity score matching of three treatment groups. [ABSTRACT FROM AUTHOR]

Abstract: The vitamin D receptor (VDR) is a member of the nuclear receptor superfamily and plays a central role in the biological actions of vitamin D. VDR regulates the expression of numerous genes involved in calcium/phosphate homeostasis, cellular proliferation and differentiation, and immune response, largely in a ligand-dependent manner. To understand the global function of the vitamin D system in physiopathological processes, great effort has been devoted to the detection of VDR in various tissues and cells, many of which have been identified as vitamin D targets. This review focuses on the tissue- and cell type-specific distribution of VDR throughout the body. [Copyright &y& Elsevier]

The kidney is the major, if not sole, site for the production of 1α,25-dihydroxyvitamin D3 (1,25(OH)2D3), the biologically active form of vitamin D that can stimulate calcium reabsorption in the kidney and may provide renoprotective benefits. The biological effects of 1,25(OH)2D3 are mediated through a nuclear hormone receptor, known as the vitamin D receptor (VDR). It is well accepted that the VDR is present in the distal renal convoluted tubule cells; however, whether VDR is present in other kidney cell types is uncertain. Using a highly specific and sensitive anti-VDR antibody, we determined its distribution in the mouse kidney by immunohistochemistry. Our results show that the VDR is not only present in the distal but is also found in the proximal tubules, but at 24-fold lower levels. The VDR was also found in the macula densa of the juxtaglomerular apparatus, glomerular parietal epithelial cells, and podocytes. In contrast, the VDR is either very low or absent in interstitial fibroblasts, glomerular mesangial cells, and juxtaglomerular cells. Thus, identification of VDR in the proximal tubule, macula densa, and podocytes suggests that 1,25(OH)2D3 plays a direct role in these cells under normal conditions. [ABSTRACT FROM AUTHOR]

Abstract: There has been a challenging work for using conventional techniques to model and control pneumatic artificial muscle (PM) due to poor knowledge and uncertainty of the process and/or complexity of the resulting mathematical model. Trying to deal with these problems, this study proposes a novel framework—Echo State Network (ESN) as a basis to implement the tasks in the PM''s modeling and control. To describe the system dynamics and the external disturbance changes with time, the online ESN adaptation scheme is presented based on the recursive least squares (RLS) algorithm. Both simulation and experimental results show that the proposed procedure has better dynamic performance and strong robustness over the other typical/classical approaches. [Copyright &y& Elsevier]

Abstract: Network covert channel is a mechanism used to transfer covert message violating security policies through network. Performance of a channel is crucial to an attacker. Some studies have improved the performance by advancing the coding mechanism, but few ones have taken account of the redundancy of covert message. This paper introduces Huffman coding scheme to compress the transferred data by exploiting redundancy, and investigates the performance of the network timing channel according to the channel capacity and covertness. A mathematical model of capacity is presented and the effects of the parameters are analyzed. The experiment examines how the network delays and the Huffman coding scheme affect the capacity and covertness, and the results demonstrate that the performance of the timing channel is improved. [Copyright &y& Elsevier]

Abstract: The active form of vitamin D, 1alpha,25-dihydroxyvitamin D3 (1,25(OH)2D3) is critical for regulation of serum calcium and phosphorus levels and for proper maintenance of bone mineralization and neuromuscular function. Biological effects of 1,25(OH)2D3 are mediated through a nuclear steroid hormone receptor, known as the vitamin D receptor (VDR). The discovery of VDR in a number of different cell and tissue types, suggests that the physiological role of vitamin D may extend beyond the regulation of calcium homeostasis and bone function. Unfortunately, identification of tissues expressing VDR has been controversial due to low abundance of the receptor and quality of the antibodies used. Therefore, we elected to characterize a panel of commercially available VDR antibodies in order to identify antibodies with high specificity and sensitivity. To address these objectives, we have used multiple immunoassays to determine VDR expression in tissues from several organs from multiple species employing tissues from VDR knockout mice as critical negative controls. Many of the antibodies tested showed nonspecific binding that can account for divergent reports. However, one antibody, identified as D-6, is highly specific and extremely sensitive. The specificity, sensitivity, and versatility of this antibody make it the preferred antibody for identifying VDR expression in target tissues using immunological methods. [Copyright &y& Elsevier]

Abstract: A two level hierarchy is employed in the design of networked control systems (NCSs) with bounded random transmission delay. At the lower level a local controller is designed to stabilize the plant. At the higher level a remote controller with the dynamic matrix control (DMC) algorithm is implemented to regulate the desirable set-point for the local controller. The conventional DMC algorithm is not applicable due to the unknown transmission delay in NCSs. To meet the requirements of a networked environment, a new remote DMC controller is proposed in this study. Two methods, maximum delayed output feedback and multi-rate sampling, are used to cope with the delayed feedback sensory data. Under the assumption that the closed-loop local system is described by one FIR model of an FIR model family, the robust stability problem of the remote DMC controller is investigated. Applying Jury’s dominant coefficient lemma and some stability results of switching discrete-time systems with multiple delays; several stability criteria are obtained in the form of simple inequalities. Finally, some numerical simulations are given to demonstrate the theoretical results. [Copyright &y& Elsevier]

Abstract: In this paper the trajectory tracking control of a human arm moving on the sagittal plane is investigated by an interdisciplinary approach with the combination of neural network mapping, evolutionary computation, and dynamic system control. The arm in the study is described by a musculoskeletal model with two degrees of freedom and six muscles, and the control signal is applied directly in the muscle space. A new control system structure is proposed to manipulate the complicated nonlinear dynamical arm motion. To design the intelligent controller, an evolutionary diagonal recurrent neural network (EDRNN) is integrated with proper performance indices, in which genetic algorithm (GA) and evolutionary program (EP) strategy are effectively integrated with the diagonal recurrent neural network (DRNN). The hybrid GA with EP strategy is applied to optimize the DRNN architecture and an adaptive dynamic back-propagation (ADBP) algorithm with momentum for the multi-input multi-output (MIMO) systems is used to obtain the network weights. The effectiveness of the control scheme is demonstrated through a simulated case study. [Copyright &y& Elsevier]

This article discusses the compensation of the transmission delay in a networked control system (NCS) with a state feedback, which possesses a randomly varying transmission delay and uncertain process parameters. The compensation is implemented by using a buffer in the actuator node and a state estimator in the controller node. A Linear Matrix Inequality-based sufficient condition for the stability of the NCS under the designed compensation is proposed. The simulation results illustrate the efficiency of the compensation method. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents an asymptotic analysis of a stochastic logistic population model with nonlinear diffusion term. The classical probability method is applied to obtain the criteria of asymptotic behavior for the considered model. The numerical simulations validate the efficiency of the theory analysis. [Copyright &y& Elsevier]

Magnesium/aluminum (Mg/Al) composites were formed by cold arc cladding (CAC) of Al alloy (AlMn1 and AlMg5) on AZ61 magnesium alloy. In the CAC of Mg/Al composites, segregation on the macroscopic and microscopic scale always occurs across the interface of the cladding layer, which affects properties of the composites. Understanding segregation mechanism in the Mg/Al composites is critical for the CAC process. Therefore, in this paper, segregation and evolution of IMCs in the Mg/Al composites were carefully investigated by SEM, EDS and XRD. Three kinds of mechanism for segregation were proposed for the interlayer of overlap region, the transition zone and the cladding layer. In the interlayer of overlap region, surfing flow of the melted base metal caused a macrosegregation zone composed of Al 3 Mg 2 and α-Al. For the transition zone, a gradient component layer consisted of Al 3 Mg 2 sub-layer, Al 12 Mg 17 sub-layer and Mg + Al 12 Mg 17 sub-layer caused the macrosegregation. Inner the cladding layer, the macrosegregation composed of Al 3 Mg 2 +Al 12 Mg 17 eutectoid structure was formed by insufficient mixing of the molten pool. Furthermore, the effect of cladding parameters on the segregation was also discussed. It is proved that lower heat input can decrease the segregations in the Mg/Al composites. The present study can provide theoretical reference and practical experience for CAC of Mg/Al composites. [Display omitted] • Mg/Al composite was prepared by CAC process to analyze the segregation mechanism. • The microstructure and composition of segregation were studied by SEM, EDS and XRD. • The formation mechanism of three types of segregation was given. •The effect of heat input on the segregation was comprehensively discussed. [ABSTRACT FROM AUTHOR]

Abstract: Thrombospondin-1 (TSP1) is an endogenous inhibitor of angiogenesis, which limits blood vessel density in normal tissues and curtails tumor growth. Previous studies of the molecular and cellular effects of TSP1 in angiogenesis have been contradictory. Here, we show that retinal endothelial cells (REC) prepared from TSP1-deficient (TSP1−/−) mice are more proliferative and migratory compared to the wild type REC. We observed up-regulation of the cell cycle regulators, including cyclin A, D1, and Cdk2, as well as the enhanced sequential activities of Src, PI3-kinase, Akt/PKB, Rac1/Cdc42 GTPases, and p38 MAP kinase in TSP1−/− REC. The increased levels of fibronectin and active Akt/PKB were also observed in retinal vasculature of TSP1−/− mice in vivo. Inhibition of Src/PI3-kinase/P38 MAP kinase activities in TSP1−/− REC resulted in decreased migration. Furthermore, TSP1−/− REC showed decreased intracellular levels of active Fyn and JNK2 without affecting caspase-3 activity. Thus, our results demonstrate that in the absence of TSP1, the proangiogenic signaling is enhanced, possibly through up-regulation of fibronectin expression. The enhanced signaling further promotes EC proliferation, migration, and survival. These novel observations support the TSP1''s role as an endogenous inhibitor of angiogenesis whose endothelium expression promotes a quiescent, differentiated phenotype. [Copyright &y& Elsevier]

Based on the recently developed algorithms for the modelling and control of bounded dynamic stochastic systems (H. Wang, J. Zhang, Bounded stochastic distributions control for pseudo ARMAX stochastic systems, IEEE Transactions on Automatic control, 486–490), this paper presents the design of a subotpimal nonlinear mean controller for bounded dynamic stochastic systems with guaranteed stability. The B-spline functional expansion based square root model is used to represent the output probability density function of the system. This is then followed by the design of a mean controller of the output distribution of the system using nonlinear output tracking concept. A nonlinear quadratic optimization is performed using the well known Hamilton–Jacobi–Bellman equation. This leads to a controller which consists of a static unit, a state feedback part and an equivalent output feedback loop. In order to achieve high precision for the output tracking, the output feedback gain is determined by a learning process, where the Lyapunov stability analysis is performed to show the asymptotic stability of the closed loop system under some conditions. A simulation example is included to demonstrate the use of the algorithm and encouraging results have been obtained. [Copyright &y& Elsevier]

Presents information on a study which discussed the mathematical model for passing sight distance (PSD) for a safe overtaking maneuver of trucks. Stages of an overtaking maneuver and definition of PSD; Definition of Intelligent Transportation Systems; Comparison with the standard given by the American Association of State Highways and Transportation Officials; Conclusions.

This paper presents a mathematical model for computing the path of any one point on a wheeled vehicle, which may be a bus, an articulated truck, or a wheeled robot, and the steering angle necessary for a reference point to travel a specified curve. This problem arises in applications that require determination of the swept space of a vehicle and in the automatic control of a mobile robot while the reference point on the vehicle moves along a specified path. The mathematical model is applicable to any dimension of a rigid vehicle or vehicle combination. It can be shown that the widely used Western Highway Institute (WHI) formula for highway design is a special case of the mathematical model presented in this paper. Based on this model, some inherent characteristics of wheeled vehicles, such as curvature, radius of instantaneous rotation of a point on the vehicle, and their relationship; and the independence of vehicle's orientation angle, steering angle, curvature, and radius of instantaneous rotation to its velocity, are also analyzed. The analytic solutions of two typical motions, circular and straight-line motions, have been developed, and the comparison of the simulation results with the existing standards has been conducted. [ABSTRACT FROM AUTHOR]

With the development of tourism and the change in urban functions, the analysis of the spatial pattern of urban tourist flows has become increasingly important. Existing studies have explored and analyzed tourist behavior well, using the appropriate digital footprint data and research methods. However, most studies have ignored internal mechanisms analysis and tourism decision making. This paper proposed a novel framework for tourist behavior analysis inspired by geo-information Tupu, including three modules of the spatiotemporal database, symptom, diagnosis, and implementation. The spatiotemporal database module is mainly used for data acquisition and data cleaning of the digital footprint of tourists. The symptom module is mainly used for revealing the spatial patterns and network structures of tourist flows. The diagnosis and implementation module is mainly used for internal mechanism analysis and tourism decision making under different tourist flow patterns. This paper applied the proposed research framework to Dengfeng City, China, using online travel diaries as the source of digital footprint data, to analyze its tourist behavior. The results were as follows: tourist flows of Dengfeng were unevenly distributed, thus forming an obvious core–periphery structure with intense internal competition and unbalanced power. The difference in tourism resources between its northern and southern areas remains a challenge for future tourism development in Dengfeng. [ABSTRACT FROM AUTHOR]

Objective: This study aims to explore the effect of YiQi GuBen capsule on improving mitochondrial dysfunction in an animal model of asthma.Methods: The mice (n = 8) were divided into four groups including control (NC), ovalbumin (OVA), dexamethasone (OVA + DEX), and YiQi GuBen (OVA + YQGB) groups. Firstly, we established an OVA-induced mouse asthma model except for the NC group, which then were treated with dexamethasone and YiQi GuBen capsule. Subsequently, HE staining and Masson staining were used for pathological analysis of mice lung tissues. Next, we used transmission electron microscopy (TEM) to observe the effect of the Yiqi Guben capsule on the ultrastructure of mitochondria. Flow cytometry was used to analyze the ROS level, membrane potential, and the number of mitochondria in lung tissue. Moreover, we analyzed the copy number of mitochondrial DNA (mtDNA) and the expression levels of activator peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) and mitochondrial transcription factor A (TFAM).Results: The results of the pathological analysis showed that after treatment with the YiQi GuBen capsule, the lung tissue damage was significantly reduced. In addition, we observed that the ultrastructural damage of mitochondria was improved. Flow cytometry proved that after treatment with the YiQi GuBen capsule, the level of ROS in the mitochondria was effectively reduced, while the mitochondrial membrane potential decreased and the number increased significantly. Moreover, we found that the copy number of mtDNA was significantly increased and the expression levels of PGC-1α and TFAM were significantly upgraded.Conclusion: This study suggests YiQi GuBen capsule can effectively improve mitochondrial dysfunction in the OVA-induced mouse model. [ABSTRACT FROM AUTHOR]

With the increasing requirements of precision agriculture for massive and various kinds of data, remote sensing technology has become indispensable in acquiring the necessary data for precision agriculture. Understanding the spatial variability of a target soil variable (i.e., soil mapping) is a critical issue in solving many agricultural problems. Field sampling is one of the most commonly used technologies for soil mapping, but sample sizes are restricted by resources, such as field labor, soil physicochemical analysis, and funding. In this paper, we proposed a sampling design method with both good spatial coverage and feature space coverage to achieve more precise spatial variability of farm field-level target soil variables for limited sample sizes. The proposed method used the super-grid to achieve good spatial coverage, and it took advantage of remote sensing products that were highly correlated with the target soil property (SOM content) to achieve good feature space coverage. For the experiments, we employed the ordinary kriging (OK) method to map the soil organic matter (SOM) content. The different sized super-grid comparison experiments showed that the 400 × 400 m2 super-grid had the highest SOM content mapping accuracy. Then, we compared the proposed method to regular grid sampling (good spatial coverage) and k-means sampling (good feature space coverage), and the experimental results indicated that the proposed method had greater potential in the selection of representative samples that could improve the SOM content mapping accuracy. [ABSTRACT FROM AUTHOR]

The ecological quality of large-scale farms is a critical determinant of crop growth. In this paper, an ecological assessment procedure suitable for agricultural regions should be developed based on an improved remote sensing ecological index (IRSEI), which introduces an integrated salinity index (ISI) tailored to the salinized soil characteristics in farming areas and incorporates ecological indices such as the greenness index (NDVI), the humidity index (WET), the dryness index (NDBSI), and the heat index (LST). The results indicate that between 2013 and 2022, the mean IRSEI increasing from 0.500 in 2013 to 0.826 in 2020 before decreasing to 0.646 in 2022. From 2013 to 2022, the area of the farm that experienced slight to significant improvements in ecological quality reached 1419.91 km2, accounting for 71.94% of the total farm area. An analysis of different land cover types revealed that the IRSEI performed more reliably than did the original RSEI method. Correlation analysis based on crop yields showed that the IRSEI method was more strongly correlated with yield than was the RSEI method. Therefore, the proposed IRSEI method offers a rapid and effective new means of monitoring ecological quality for agricultural planting areas characterized by soil salinization, and it is more effective than the traditional RSEI method. [ABSTRACT FROM AUTHOR]

Considering the precise model information of the aerospace model is not always available under the effect of external disturbance and model uncertainty, a new data‐driven point‐to‐point iterative learning control (PTPILC) method is proposed for aerospace vehicles to track the predetermined trajectory. Firstly, the system of the aerospace vehicle is converted into a discrete form without any omission, which reflects the dynamics of the original system by input and output data. Then, the objective function of the tracking error is proposed in the quadratic form to facilitate the application of the conjugate gradient algorithm, which develops an improved data‐driven PTPILC method. And the convergence analysis of the proposed method is presented. Furthermore, the control parameters are optimized to make the proposed method more robust against different parameter deviations. Finally, the effectiveness of the proposed method is illustrated by different simulations. [ABSTRACT FROM AUTHOR]

This article proposes a new three-dimensional (3D) guidance algorithm for a two-stage solid rocket-powered launch vehicle in the ascent phase. The method consists of a longitudinal and lateral cooperative online trajectory generation method and a model predictive control (MPC) based tracking method. First, we introduced a new variable, named lateral displacement distance, to describe lateral motion. After decoupling the 3D dynamics into the longitudinal and lateral movements, the lateral distance was calculated by minimum order polynomials, as well as the altitude in the longitudinal plane. The multiple constraints were satisfied accordingly. This new representation transforms the online trajectory generation problem into a single-parameter root-finding problem, which is solved online by Newton's method. Second, the traditional energy management method, which usually works in the last phase of multistage solid rockets, was extended to all stages. A proportion was put forward to allocate the energy management demand to the two stages of solid rockets. This strategy can enlarge the energy management capacity of solid rockets. Third, the MPC method was adopted to obtain the tracking guidance law to lessen the effect of uncertain parameters. The subsequent stability analysis shows that the MPC-based tracking controller is closed-loop stable and can handle the constraints and parameter uncertainties simultaneously. Finally, the effectiveness and robustness were verified by validating a two-stage solid rocket's ascent phase flight under aerodynamic uncertainties and initial state deviations. In comparison to the existing energy management method, the incorporation of the sideslip angle design in this study renders solid rockets more capable at energy management. The proposed algorithm can accurately steer the rocket vehicle to the transition window. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM) is the most malignant brain tumor with unmet therapeutic demand. The blood‐brain‐barrier (BBB) and tumor heterogeneity limit the treatment effectiveness of various interventions. Here, an ultrasound augmented chemo/immuno therapy for GBM using a neutrophil‐delivered nanosensitizer, is developed. The sensitizer is composed of a ZnGa2O4:Cr3+ (ZGO) core for persistent luminescence imaging and a hollow sono‐sensitive TiO2 shell to generate reactive oxygen species (ROS) for controlled drug release. Immune checkpoint inhibitor (Anti‐PD‐1 antibody) is trapped in the interior of the porous ZGO@TiO2 with paclitaxel (PTX) loaded liposome encapsulation to form ZGO@TiO2@ALP. Delivered by neutrophils (NEs), ZGO@TiO2@ALP‐NEs can penetrate through BBB for GBM accumulation. After intravenous injection, ultrasound irradiation at GBM sites initiates ROS generation from ZGO@TiO2@ALP, leading to liposome destruction for PTX and anti‐PD‐1 antibody release to kill tumors and induce local inflammation, which in‐turn attractes more ZGO@TiO2@ALP‐NEs to migrate into tumor sites for augmented and sustained therapy. The treatment enhances the survival rate of the GBM bearing mice from 0% to 40% and endows them with long‐term immuno‐surveillance for tumor recurrence, providing a new approach for precision therapy against GBM and other cancers. [ABSTRACT FROM AUTHOR]

Image segmentation is an important process and a prerequisite for object-based image analysis. Thus, evaluating the performance of segmentation algorithms is essential to identify effective segmentation methods and to optimize the scale. In this paper, we propose an unsupervised evaluation (UE) method using the area-weighted variance (WV) and Jeffries-Matusita (JM) distance to compare two image partitions to evaluate segmentation quality. The two measures were calculated based on the local measure criteria, and the JM distance was improved by considering the contribution of the common border between adjacent segments and the area of each segment in the JM distance formula, which makes the heterogeneity measure more effective and objective. Then the two measures were presented as a curve when changing the scale from 8 to 20, which can reflect the segmentation quality in both over- and under-segmentation. Furthermore, the WV and JM distance measures were combined by using three different strategies. The effectiveness of the combined indicators was illustrated through supervised evaluation (SE) methods to clearly reveal the segmentation quality and capture the trade-off between the two measures. In these experiments, the multiresolution segmentation (MRS) method was adopted for evaluation. The proposed UE method was compared with two existing UE methods to further confirm their capabilities. The visual and quantitative SE results demonstrated that the proposed UE method can improve the segmentation quality. [ABSTRACT FROM AUTHOR]

Image segmentation is an important process and a prerequisite for object-based image analysis, but segmenting an image into meaningful geo-objects is a challenging problem. Recently, some scholars have focused on hybrid methods that employ initial segmentation and subsequent region merging since hybrid methods consider both boundary and spatial information. However, the existing merging criteria (MC) only consider the heterogeneity between adjacent segments to calculate the merging cost of adjacent segments, thus limiting the goodness-of-fit between segments and geo-objects because the homogeneity within segments and the heterogeneity between segments should be treated equally. To overcome this limitation, in this paper a hybrid remote-sensing image segmentation method is employed that considers the objective heterogeneity and relative homogeneity (OHRH) for MC during region merging. In this paper, the OHRH method is implemented in five different study areas and then compared to our region merging method using the objective heterogeneity (OH) method, as well as the full lambda-schedule algorithm (FLSA). The unsupervised evaluation indicated that the OHRH method was more accurate than the OH and FLSA methods, and the visual results showed that the OHRH method could distinguish both small and large geo-objects. The segments showed greater size changes than those of the other methods, demonstrating the superiority of considering within- and between-segment heterogeneity in the OHRH method. [ABSTRACT FROM AUTHOR]

This paper focuses on the guidance of an unpowered reusable launch vehicle (RLV) with aerosurface failure in the terminal area energy management (TAEM) phase. The aerosurface failure will limit the bank capability, and has a great influence on the range and turning radius of RLV. To this end, a new TAEM guidance scheme with the ability of online profile reconstruction is proposed in this paper for the bank-constrained RLV. The 3-dimensional (3D) profile is reconstructed online by directly adjusting the parameters of the dynamic pressure profile and the two-external-tangent-circle-based ground track profile. As the coupling between vertical and lateral motion is considered in the trajectory propagation, the reconstruction accuracy is guaranteed. Then, a closed-loop TAEM guidance law is proposed to track the reconstructed 3D profile. The effectiveness and robustness of the guidance scheme are verified by numerical simulations with a variety of initial states and model deviations. [ABSTRACT FROM AUTHOR]

In this paper, the linear parameter varying (LPV) reliable non-fragile control for the hypersonic vehicle (HV) is studied in case of disturbance and controller gain variations. Due to the dramatic and complex change of the HV longitudinal dynamics, a polytopic LPV model is constructed for the HV system stability analysis and controller design in a large flight envelope. Then, a disturbance observer (DOB)-based non-fragile controller for HV system with disturbance and unknown controller uncertainty is designed to guarantee the closed-loop stability and control performance under an adequate level of reliability, which is formed with two parts. One part is a DOB to compensate the uncertain dynamics and disturbance. The other is a robust non-fragile controller, which is designed based on a novel robust reliability method to deal with controller uncertainties, and obtained by carrying out reliability-based linear matrix inequality optimization. The presented controller for HV can provide the robustness as well as an excellent performance under the condition that the prescribed reliability degree is satisfied. Finally, numerical simulation for an HV demonstrates the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This paper aims to study the new methodology of nonlinear system identification problem of one–stage spur gearbox. Consider the influence of the complicated factors, the model of a one–stage spur gearbox obviously possesses the nonlinear dynamic characteristics. To identify the nonlinear system, a pseudo–linear neural network (PNN) based on the idea of gained–scheduling techniques and extended linearization model is presented. The PNN consists of multilayer architectures, in which the first hidden layers and output layers are the same as those used in a multilayer perceptron (MLP). The second hidden layers are composed of neurons with multiplication function, whose outputs are the products of the inputs. In order to improve the identification effectiveness, an extended Kalman filter (EKF) algorithm is employed to train the weights of the PNN, and model verification of a class of nonlinear system is fulfilled via computer simulation. The PNN identification approach of a one–stage spur gearbox in no–load and load condition are based on the experimental data, which are subdivided into a training set and a testing set. The training set is used for identification the PNN model of displacement and acceleration, while the testing set is applied to examine the classification accuracy of the proposed PNN model. To compare the identification precision, the diagonal recurrent neural network (DRNN) and MLP based on EKF methods are applied to model the same gearbox, respectively. The final results of identification and comparison of the one–stage spur gearbox demonstrate that the proposed PNN paradigm has the applicability and good performance. [ABSTRACT FROM AUTHOR]

Based on the digital footprint data, exploring the differences in tourist market structure and driving factors before and after COVID-19 is important for identifying tourist market demand and optimizing tourism product supply in the post-pandemic era. Most of the existing studies have explored the impact of the pandemic on the tourist market in well-known or large cities and have provided suggestions for tourism recovery. However, these suggestions are not entirely applicable to smaller cities. Small cities have a single level of tourism product, high homogeneity of tourism resources, small tourist market scale, and high volatility of the tourism industry. Therefore, it is necessary to study the differences in the tourist market structure of small cities and its driving factors before and after the pandemic and to propose targeted measures for the tourism recovery in the post-pandemic period. This paper, taking small cities as the study area and using online travel diaries as the data source, analyzed the differences in the spatial and temporal structures of tourist markets and their driving factors in Dengfeng and Kaifeng, China, before and after the pandemic. Then, countermeasures for tourism industry recovery in the post-pandemic era were proposed. The results were as follows: the difference in the tourism off-peak season increased after the pandemic, and the concentration of tourist market spatial distribution in Dengfeng showed a decreasing trend while that in Kaifeng showed an increasing trend. In addition to region traffic, the driving effects of leisure time, climate comfort and residents' income level weakened after the outbreak. Dengfeng and Kaifeng can enhance the tourist market tendency and attractiveness by creating special indoor tourism projects, strengthening tourism product promotion and marketing and enhancing the facilities related to self-driving tours. [ABSTRACT FROM AUTHOR]